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Objective Large-scale studies have revolutionized biomedical research, and neurocognitive tests can help elucidate the biological basis of neuropsychiatric diseases. However, studies have predominantly been conducted in Western settings. We describe the development and validation of a computerized battery (PennCNB) with the Xhosa population of South Africa. Method Individuals with schizophrenia (n = 525) and a normative comparison group (n = 744) were balanced on age, sex, education, and region. Participants provided blood samples, were assessed psychiatrically, and were administered a PennCNB translation to isiXhosa, including measures of executive functions, episodic memory, complex cognition, social cognition, and sensorimotor speed. Feasibility was examined with test completion rates and input from administrators, and psychometric structural validity and associations with clinical and demographic characteristics were examined. Results Tests were well tolerated by participants, as >87% had one (or fewer) test missing. Results suggested a similar factor structure to prior PennCNB studies in Western contexts, and expected age and sex effects were apparent. Furthermore, a similar profile of schizophrenia was observed, with neurocognitive deficits most pronounced for executive functions, especially attention, as well as memory, social cognition, and motor speed relative to complex cognition and sensorimotor speed. Conclusions Results support the feasibility of implementing a culturally adapted computerized neurocognitive battery in sub-Saharan African settings and provide evidence supporting the concurrent validity of the translated instrument. Thus, the PennCNB is implementable on a large scale in non-Western contexts, shows expected factor structure, and can detect cognitive deficits associated with neuropsychiatric disorders. Obtaining valid measures of cognition by nonspecialized proctors is especially suitable in resource-limited settings, where traditional testing is prohibitive. Future work should establish normative standards, test-retest reliability, and sensitivity to treatment. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

The Marine Resiliency Study-II examined changes in symptomatology across a deployment cycle to Afghanistan. U.S. Servicemembers (N=1041) received clinical testing at two time points either bracketing a deployment (855) or not (186). Factor analyses were used to generate summary and change scores from Time 1 to Time 2. A between-subject design was used to examine changes across the deployment cycle with deployment (low-trauma, high-trauma, and non-deployed) and social support (low vs. high) as the grouping variables. Insomnia increased post-deployment regardless of deployment trauma (std. effect for high-trauma and low-trauma=0.39 and 0.26, respectively). Only the high-trauma group showed increased PTSD symptoms and non-perspective-taking (std. effect=0.40 and 0.30, respectively), while low-trauma showed decreased anxiety symptoms after deployment (std. effect=-0.17). These associations also depend on social support, with std. effects ranging from-0.22 to 0.51. When the groups were compared, the high-trauma deployed group showed significantly worse PTSD and non-perspective-taking than all other groups. Similar to studies in other military divisions, increased clinical symptoms were associated with high deployment stress in active duty Servicemembers, and social support shows promise as a moderator of said association.

Traditional "paper-and-pencil" testing is imprecise in measuring speed and hence limited in assessing performance efficiency, but computerized testing permits precision in measuring itemwise response time. We present a method of scoring performance efficiency (combining information from accuracy and speed) at the item level. Using a community sample of 9,498 youths age 8-21, we calculated item-level efficiency scores on 4 neurocognitive tests, and compared the concurrent, convergent, discriminant, and predictive validity of these scores with simple averaging of standardized speed and accuracy-summed scores. Concurrent validity was measured by the scores' abilities to distinguish men from women and their correlations with age; convergent and discriminant validity were measured by correlations with other scores inside and outside of their neurocognitive domains; predictive validity was measured by correlations with brain volume in regions associated with the specific neurocognitive abilities. Results provide support for the ability of itemwise efficiency scoring to detect signals as strong as those detected by standard efficiency scoring methods. We find no evidence of superior validity of the itemwise scores over traditional scores, but point out several advantages of the former. The itemwise efficiency scoring method shows promise as an alternative to standard efficiency scoring methods, with overall moderate support from tests of 4 different types of validity. This method allows the use of existing item analysis methods and provides the convenient ability to adjust the overall emphasis of accuracy versus speed in the efficiency score, thus adjusting the scoring to the real-world demands the test is aiming to fulfill. (PsycINFO Database Record

Disruption of executive function is present in many neuropsychiatric disorders. However, determining the specificity of executive dysfunction across these disorders is challenging given high comorbidity of conditions. Here the authors investigate executive system deficits in association with dimensions of psychiatric symptoms in youth using a working memory paradigm. The authors hypothesize that common and dissociable patterns of dysfunction would be present.The authors studied 1,129 youths who completed a fractal n-back task during functional magnetic resonance imaging at 3-T as part of the Philadelphia Neurodevelopmental Cohort. Factor scores of clinical psychopathology were calculated using an item-wise confirmatory bifactor model, describing overall psychopathology as well as four orthogonal dimensions of symptoms: anxious-misery (mood and anxiety), behavioral disturbance (attention deficit hyperactivity disorder and conduct disorder), psychosis-spectrum symptoms, and fear (phobias). The effect of psychopathology dimensions on behavioral performance and executive system recruitment (2-back0-back) was examined using both multivariate (matrix regression) and mass-univariate (linear regression) analyses.Overall psychopathology was associated with both abnormal multivariate patterns of activation and a failure to activate executive regions within the cingulo-opercular control network, including the frontal pole, cingulate cortex, and anterior insula. In addition, psychosis-spectrum symptoms were associated with hypoactivation of the left dorsolateral prefrontal cortex, whereas behavioral symptoms were associated with hypoactivation of the frontoparietal cortex and cerebellum. In contrast, anxious-misery symptoms were associated with widespread hyperactivation of the executive network.These findings provide novel evidence that common and dissociable deficits within the brain's executive system are present in association with dimensions of psychopathology in youth.

Adults with psychotic disorders have dysconnectivity in critical brain networks, including the default mode (DM) and the cingulo-opercular (CO) networks. However, it is unknown whether such deficits are present in youth with less severe symptoms. We conducted a multivariate connectome-wide association study examining dysconnectivity with resting state functional magnetic resonance imaging in a population-based cohort of 188 youths aged 8-22 years with psychosis-spectrum (PS) symptoms and 204 typically developing (TD) comparators. We found evidence for multi-focal dysconnectivity in PS youths, implicating the bilateral anterior cingulate, frontal pole, medial temporal lobe, opercular cortex and right orbitofrontal cortex. Follow-up seed-based and network-level analyses demonstrated that these results were driven by hyper-connectivity among DM regions and diminished connectivity among CO regions, as well as diminished coupling between frontal and DM regions. Collectively, these results provide novel evidence for functional dysconnectivity in PS youths, which show marked correspondence to abnormalities reported in adults with established psychotic disorders.

Cannabis use in youth is rising and has been linked to deficits in cognitive functioning. However, cognitive findings have primarily been based on small samples of users seeking treatment, and few studies have evaluated cognition in occasional cannabis users. Here, we examined 4,568 adolescents and young adults (ages 14-21 years) drawn from the Philadelphia Neurodevelopmental Cohort, a prospective, population-based study. Participants were classified as cannabis Non-Users (n = 3,401), Occasional Users (twice per week or less; n = 940), or Frequent Users (>3 times per week; n = 227). Mixed-model analyses examined main effects of cannabis use and interactions between age and cannabis use on cognitive functioning. There was a significant interaction between cannabis group and age such that adolescent (but not young adult) Frequent Users performed worse than Non-Users on measures of executive control (p = .002). Earlier age of cannabis use was associated with worse performance in executive control in Occasional Users (p = .04). Unexpectedly, Occasional Users exhibited better executive control, memory, and social cognition than Non-Users (ps < .05). Although mild executive control deficits in adolescent frequent users and a relation between early cannabis initiation and cognitive performance are partially consistent with prior research, cognitive deficits were not found in other hypothesized domains in this community-based sample. Moreover, occasional cannabis users displayed equivalent or even slightly better executive control, social-cognitive, and memory abilities compared with nonusers, suggesting complex relationships between cannabis use and cognition in youth. Longitudinal studies with community samples are needed to identify variables affecting risk and resilience to cognitive deficits associated with cannabis. (PsycINFO Database Record

Several independent studies have demonstrated that small amounts of in-scanner motion systematically bias estimates of resting-state functional connectivity. This confound is of particular importance for studies of neurodevelopment in youth because motion is strongly related to subject age during this period. Critically, the effects of motion on connectivity mimic major findings in neurodevelopmental research, specifically an age-related strengthening of distant connections and weakening of short-range connections. Here, in a sample of 780 subjects ages 8-22, we re-evaluate patterns of change in functional connectivity during adolescent development after rigorously controlling for the confounding influences of motion at both the subject and group levels. We find that motion artifact inflates both overall estimates of age-related change as well as specific distance-related changes in connectivity. When motion is more fully accounted for, the prevalence of age-related change as well as the strength of distance-related effects is substantially reduced. However, age-related changes remain highly significant. In contrast, motion artifact tends to obscure age-related changes in connectivity associated with segregation of functional brain modules; improved preprocessing techniques allow greater sensitivity to detect increased within-module connectivity occurring with development. Finally, we show that subject's age can still be accurately estimated from the multivariate pattern of functional connectivity even while controlling for motion. Taken together, these results indicate that while motion artifact has a marked and heterogeneous impact on estimates of connectivity change during adolescence, functional connectivity remains a valuable phenotype for the study of neurodevelopment.

BackgroundThe contribution of ‘environment’ has been investigated across diverse and multiple domains related to health. However, in the context of large-scale genomic studies the focus has been on obtaining individual-level endophenotypes with environment left for future decomposition. Geo-social research has indicated that environment-level variables can be reduced, and these composites can then be used with other variables as intuitive, precise representations of environment in research.MethodUsing a large community sample (N = 9498) from the Philadelphia area, participant addresses were linked to 2010 census and crime data. These were then factor analyzed (exploratory factor analysis; EFA) to arrive at social and criminal dimensions of participants' environments. These were used to calculate environment-level scores, which were merged with individual-level variables. We estimated an exploratory multilevel structural equation model (MSEM) exploring associations among environment- and individual-level variables in diverse communities.ResultsThe EFAs revealed that census data was best represented by two factors, one socioeconomic status and one household/language. Crime data was best represented by a single crime factor. The MSEM variables had good fit (e.g. comparative fit index = 0.98), and revealed that environment had the largest association with neurocognitive performance (β = 0.41, p < 0.0005), followed by parent education (β = 0.23, p < 0.0005).ConclusionsEnvironment-level variables can be combined to create factor scores or composites for use in larger statistical models. Our results are consistent with literature indicating that individual-level socio-demographic characteristics (e.g. race and gender) and aspects of familial social capital (e.g. parental education) have statistical relationships with neurocognitive performance.

Background Diffusion tensor imaging (DTI) is applied in investigation of brain biomarkers for neurodevelopmental and neurodegenerative disorders. However, the quality of DTI measurements, like other neuroimaging techniques, is susceptible to several confounding factors (e.g., motion, eddy currents), which have only recently come under scrutiny. These confounds are especially relevant in adolescent samples where data quality may be compromised in ways that confound interpretation of maturation parameters. The current study aims to leverage DTI data from the Philadelphia Neurodevelopmental Cohort (PNC), a sample of 1601 youths with ages of 8–21 who underwent neuroimaging, to: 1) establish quality assurance (QA) metrics for the automatic identification of poor DTI image quality; 2) examine the performance of these QA measures in an external validation sample; 3) document the influence of data quality on developmental patterns of typical DTI metrics. Methods All diffusion-weighted images were acquired on the same scanner. Visual QA was performed on all subjects completing DTI; images were manually categorized as Poor, Good, or Excellent. Four image quality metrics were automatically computed and used to predict manual QA status: Mean voxel intensity outlier count (MEANVOX), Maximum voxel intensity outlier count (MAXVOX), mean relative motion (MOTION) and temporal signal-to-noise ratio (TSNR). Classification accuracy for each metric was calculated as the area under the receiver-operating characteristic curve (AUC). A threshold was generated for each measure that best differentiated visual QA status and applied in a validation sample. The effects of data quality on sensitivity to expected age effects in this developmental sample were then investigated using the traditional MRI diffusion metrics: fractional anisotropy (FA) and mean diffusivity (MD). Finally, our method of QA is compared with DTIPrep. Results TSNR (AUC = 0.94) best differentiated Poor data from Good and Excellent data. MAXVOX (AUC = 0.88) best differentiated Good from Excellent DTI data. At the optimal threshold, 88% of Poor data and 91% Good/Excellent data were correctly identified. Use of these thresholds on a validation dataset (n = 374) indicated high accuracy. In the validation sample 83% of Poor data and 94% of Excellent data was identified using thresholds derived from the training sample. Both FA and MD were affected by the inclusion of poor data in an analysis of an age, sex and race matched comparison sample. In addition, we show that the inclusion of poor data results in significant attenuation of the correlation between diffusion metrics (FA and MD) and age during a critical neurodevelopmental period. We find higher correspondence between our QA method and DTIPrep for Poor data, but we find our method to be more robust for apparently high-quality images. Conclusion Automated QA of DTI can facilitate large-scale, high-throughput quality assurance by reliably identifying both scanner and subject induced imaging artifacts. The results present a practical example of the confounding effects of artifacts on DTI analysis in a large population-based sample, and suggest that estimates of data quality should not only be reported but also accounted for in data analysis, especially in studies of development.

© 2015 APA, all rights reserved). Visuospatial processing is a commonly assessed neurocognitive domain with deficits linked to dysfunction in right posterior regions of the brain. With the growth of large-scale clinical research studies, there is an increased need for efficient and scalable assessments of neurocognition, including visuospatial processing. The purpose of the current study was to use a novel method that combines item response theory (IRT) and computerized adaptive testing (CAT) approaches to create an abbreviated form of the computerized Penn Line Orientation Test (PLOT). The 24-item PLOT was administered to 8,498 youths (aged 8-21 years) as part of the Philadelphia Neurodevelopmental Cohort study and, by Web-based data collection, in an independent sample of 4,593 adults from Great Britain as part of a TV documentary. IRT-based CAT simulations were used to select the best PLOT items for an abbreviated form by performing separate simulations in each group and choosing only items that were selected as useful (i.e., high item discrimination and in the appropriate difficulty range) in at least 1 of the simulations. Fifteen items were chosen for the final, short form of the PLOT, indicating substantial agreement among the models in how they evaluated each item's usefulness. Moreover, this abbreviated version performed comparably to the full version in tests of sensitivity to age and sex effects. This abbreviated version of the PLOT cuts administration time by 50% without detectable loss of information, which points to its feasibility for large-scale clinical and genomic studies. (PsycINFO Database Record

The Philadelphia Neurodevelopmental Cohort (PNC) is a large-scale study of child development that combines neuroimaging, diverse clinical and cognitive phenotypes, and genomics. Data from this rich resource is now publicly available through the Database of Genotypes and Phenotypes (dbGaP). Here we focus on the data from the PNC that is available through dbGaP and describe how users can access this data, which is evolving to be a significant resource for the broader neuroscience community for studies of normal and abnormal neurodevelopment.

The Philadelphia Neurodevelopmental Cohort (PNC) is a large-scale, NIMH funded initiative to understand how brain maturation mediates cognitive development and vulnerability to psychiatric illness, and understand how genetics impacts this process. As part of this study, 1445 adolescents ages 8-21 at enrollment underwent multimodal neuroimaging. Here, we highlight the conceptual basis for the effort, the study design, and the measures available in the dataset. We focus on neuroimaging measures obtained, including T1-weighted structural neuroimaging, diffusion tensor imaging, perfusion neuroimaging using arterial spin labeling, functional imaging tasks of working memory and emotion identification, and resting state imaging of functional connectivity. Furthermore, we provide characteristics regarding the final sample acquired. Finally, we describe mechanisms in place for data sharing that will allow the PNC to become a freely available public resource to advance our understanding of normal and pathological brain development.

Objective Puberty is the defining process of adolescence, and is accompanied by divergent trajectories of behavior and cognition for males and females. Here we examine whether sex differences exist in the effect of puberty on the morphology of the hippocampus and amygdala. Method T1-weighted structural neuroimaging was performed in a sample of 524 pre- or postpubertal individuals ages 10 to 22 years. Hippocampal and amygdala volume and shape were quantified using the Functional Magnetic Resonance Imaging of the Brain (FMRIB) Software Library (FSL) FIRST procedure and scaled by intracranial volume. The effects on regional volume of age, sex, puberty, and their interactions were examined using linear regression. Postpubertal sex differences were examined using a vertex analysis. Results Prepubertal males and females had similar hippocampal volumes, whereas postpubertal females had significantly larger bilateral hippocampi, resulting in a significant puberty-by-sex interaction even when controlling for age and age-by-sex. This effect was regionally specific and was not apparent in the amygdala. Vertex analysis revealed that postpubertal differences were most prominent in the lateral aspect of the hippocampus bilaterally, corresponding to the CA1 subfield. Conclusions These results establish that there are regionally specific sex differences in the effect of puberty on the hippocampus. These findings are relevant for the understanding of psychiatric disorders that have both hippocampal dysfunction and prominent gender disparities during adolescence.

The continuum view of the psychosis spectrum (PS) implies that, in population-based samples, PS symptoms should be associated with neural abnormalities similar to those found in help-seeking clinical risk individuals and in schizophrenia. To our knowledge, functional neuroimaging has not previously been applied in large population-based PS samples and can help us understand the neural architecture of psychosis more broadly and identify brain phenotypes beyond symptoms that are associated with the extended psychosis phenotype.To examine the categorical and dimensional relationships of PS symptoms to prefrontal hypoactivation during working memory and to amygdala hyperactivation during threat emotion processing.The Philadelphia Neurodevelopmental Cohort is a genotyped, prospectively accrued, population-based sample of almost 10,000 youths who received a structured psychiatric evaluation and a computerized neurocognitive battery. The study was conducted at an academic and children's hospital health care network, between November 1, 2009 to November 30, 2011. A subsample of 1445 youths underwent neuroimaging, including functional magnetic resonance imaging tasks examined herein. Participants were youth aged 11 to 22 years old identified through structured interview as having PS features (PS group) (n = 260) and typically developing (TD) comparison youth without significant psychopathology (TD group) (n = 220).Two functional magnetic resonance imaging paradigms were used: a fractal n-back working memory task probing executive system function and an emotion identification task probing amygdala responses to threatening faces.In the n-back task, working memory evoked lower activation in the PS group than the TD group throughout the executive control circuitry, including dorsolateral prefrontal cortex (cluster-corrected P .05). Within the PS group, dorsolateral prefrontal cortex activation correlated with cognitive deficits (r = .32, P .001), but no correlation was found with positive symptom severity. During emotion identification, PS demonstrated elevated responses to threatening facial expressions in amygdala, as well as left fusiform cortex and right middle frontal gyrus (cluster-corrected P .05). The response in the amygdala correlated with positive symptom severity (r = .16, P = .01) but not with cognitive deficits.The pattern of functional abnormalities observed in the PS group is similar to that previously found in schizophrenia and help-seeking risk samples. Specific circuit dysfunction during cognitive and emotion-processing tasks is present early in the development of psychopathology and herein could not be attributed to chronic illness or medication confounds. Hypoactivation in executive circuitry and limbic hyperactivation to threat could reflect partly independent risk factors for PS symptoms, with the former relating to cognitive deficits that increase the risk for developing psychotic symptoms and the latter contributing directly to positive psychotic symptoms.